Merge #1959 into 1.6.x branch (#1963)

* Loosen dz scaling application to use the longest forecast period scaling coefficient available if no forecast period has a greater length than the forecast itself.

* Adjustments to doc-strings as per review.

improver/calibration/dz_rescaling.py

@@ -373,7 +373,9 @@ def _create_forecast_period_constraint(
         """Create a forecast period constraint to identify the most appropriate
         forecast period from the scaled_dz to extract. The most appropriate scaled dz
         is selected by choosing the nearest forecast period that is greater than or
-        equal to the forecast period of the forecast.
+        equal to the forecast period of the forecast. If no forecast periods in the
+        scaled dz cube are greater than the forecast period of the forecast, the
+        longest available forecast period is used.
 
         Args:
             forecast: Forecast to be adjusted using dz rescaling.
@@ -391,16 +393,12 @@ def _create_forecast_period_constraint(
             - forecast.coord("forecast_period").points
         )
 
-        if not any(fp_diff >= 0):
-            (fp_hour,) = forecast.coord("forecast_period").points / SECONDS_IN_HOUR
-            msg = (
-                "There is no scaled version of the difference in altitude for "
-                f"a forecast period greater than or equal to {fp_hour}"
-            )
-            raise ValueError(msg)
+        if any(fp_diff >= 0):
+            fp_index = np.argmax(fp_diff >= 0)
+            chosen_fp = scaled_dz.coord("forecast_period").points[fp_index]
+        else:
+            chosen_fp = scaled_dz.coord("forecast_period").points[-1]
 
-        fp_index = np.argmax(fp_diff >= 0)
-        chosen_fp = scaled_dz.coord("forecast_period").points[fp_index]
         return iris.Constraint(forecast_period=chosen_fp)
 
     @staticmethod

improver/cli/apply_dz_rescaling.py

@@ -56,8 +56,10 @@ def process(
             forecast period and forecast reference_time_hour pair within the
             rescaling cube are chosen using the forecast reference time hour from
             the forecast and the nearest forecast period that is greater than or
-            equal to the forecast period of the forecast. This cube is generated
-            using the estimate_dz_rescaling CLI.
+            equal to the forecast period of the forecast. However, if the forecast
+            period of the forecast exceeds all forecast periods within the rescaling
+            cube, the scaling factor from the maximum forecast period is used.
+            This cube is generated using the estimate_dz_rescaling CLI.
         site_id_coord (str):
             The name of the site ID coordinate. This defaults to 'wmo_id'.
 

improver_tests/calibration/dz_rescaling/test_apply_dz_rescaling.py

@@ -158,7 +158,7 @@ def _create_scaling_factor_cube(
 
 
 @pytest.mark.parametrize("wmo_id", [True, False])
-@pytest.mark.parametrize("forecast_period", [6, 18])
+@pytest.mark.parametrize("forecast_period", [6, 18, 30])
 @pytest.mark.parametrize("frt_hour", [3, 12])
 @pytest.mark.parametrize("scaling_factor", [0.99, 1.01])
 @pytest.mark.parametrize("forecast_period_offset", [0, -1, -5])
@@ -177,9 +177,11 @@ def test_apply_dz_rescaling(
     contains the scaling_factor value.
     forecast_period_offset (hours) adjusts the forecast period coord on the forecast
     cube to ensure the plugin always snaps to the next largest forecast_time when the
-    precise point is not available.
+    precise point is not available except when the forecast period of the forecast
+    exceeds all forecast periods within the scaling factor cube. In this case, the
+    last forecast period within the scaling factor cube will be used.
     frt_hour_offset (hours) alters the forecast reference time hour within the forecast
-    whilst the forececast reference time hour of the scaling factor remains the same.
+    whilst the forecast reference time hour of the scaling factor remains the same.
     This checks that the a mismatch in the forecast reference time hour can still
     result in a match, if a leniency is specified.
     """
@@ -199,8 +201,11 @@ def test_apply_dz_rescaling(
         forecast_period + forecast_period_offset,
         forecast,
     )
+    # Use min(fp, 24) here to ensure that the scaling cube contains
+    # the scaling factor for the last forecast_period if the specified
+    # forecast period is beyond the T+24 limit of the scaling cube.
     scaling_factor = _create_scaling_factor_cube(
-        frt_hour, forecast_period, scaling_factor
+        frt_hour, min(forecast_period, 24), scaling_factor
     )
 
     kwargs = {}
@@ -275,10 +280,7 @@ def test_mismatching_sites():
 
 @pytest.mark.parametrize(
     "forecast_period,frt_hour,exception",
-    [
-        (25, 3, "forecast period greater than or equal to 25"),
-        (7, 1, "forecast reference time hour equal to 1"),
-    ],
+    [(7, 1, "forecast reference time hour equal to 1")],
 )
 def test_no_appropriate_scaled_dz(forecast_period, frt_hour, exception):
     """Test an exception is raised if no appropriate scaled version of the difference